from cars import training_points, training_labels, testing_points, testing_labels
from sklearn.tree import DecisionTreeClassifier

classifier = DecisionTreeClassifier()

classifier.fit(training_points, training_labels)

print(classifier.score(testing_points, testing_labels))

def warn(*args, **kwargs):
    pass
import warnings
warnings.warn = warn
from cars import training_points, training_labels, testing_points, testing_labels
import warnings
from sklearn.ensemble import RandomForestClassifier

classifier = RandomForestClassifier(n_estimators = 2000, random_state = 0)
classifier.fit(training_points, training_labels)
print(classifier.score(testing_points, testing_labels))